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Computer Science and Programming

Computer Science and Programming

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Channel specialized for advanced topics of: * Artificial intelligence, * Machine Learning, * Deep Learning, * Computer Vision, * Data Science * Python Admin: @otchebuch Memes: @memes_programming Ads: @Source_Ads, https://telega.io/c/computer_science

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Computer Science and Programming (@computer_science_and_programming) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 138 807 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 817-o'rinni va Italiya mintaqasida 89-o'rinni egallagan.

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невідомо sanasidan buyon loyiha tez o‘sib, 138 807 obunachiga ega bo‘ldi.

02 Noyabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -985 ga, so‘nggi 24 soatda esa -42 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

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Yuqori yangilanish chastotasi (oxirgi ma’lumot 03 Noyabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

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Postlar arxiv
Well explained Tutorial series: Transfer Learning, Natural Language Processing, Text classification, etc from Sebastian Ruder.

Another great lecture series from Stanford. CS224N Natural Language Processing with Deep Learning | Winter 2019

This is a great place to share resources with other, here is Global Artificial Community platform, where you can find questions, discussions solutions only about #AI. And also there are some upcoming great features, which will really usefull for us. Visit, login, share and be more related with #AI stuff.

Great article from Analytics Vidhya: "A Step-by-Step NLP Guide to Learn ELMo for Extracting Features from Text". * However you can utilize ElMo for several domains: - Machine Translation - Language Modeling - Text Summarization - Named Entity Recognition - Question-Answering Systems

Discover open source Deep Learning code and pretrained models. Deep learning researchers easily find pre-trained models for a variety of platforms and uses. Great resource

De Facto list of book from Geeks of Deep Learning. Happy learning from up-to-date resources. Updated list 2019
De Facto list of book from Geeks of Deep Learning. Happy learning from up-to-date resources. Updated list 2019

Let's travel zoopark of GANs. Here is listed more than 300 (~) types of GANs family for different purposes. Happy travel and enjoy

Interpretable Machine Learning "A Guide for Making Black Box Models Explainable" by Christoph Molnar
Interpretable Machine Learning "A Guide for Making Black Box Models Explainable" by Christoph Molnar

Web data scraping with Python by Brian Keegan University of Colorado, 2019. Enjoy scraping web with detailed tutorial

Now introducing Chrome extension that makes it easy to find code when browsing arxiv.org or Google Scholar: